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IMA Newsletter #355

May 2006

2005-2006 Program

Imaging

News and Notes

William Massey wins 2006 Blackwell–Tapia Prize

The National Blackwell–Tapia Committee is pleased to announce that the 2006 Blackwell–Tapia Prize will be awarded to William Massey, Edwin S. Wiley Professor of Operations Research and Financial Engineering at Princeton University. This prize is awarded every other year in honor of the legacy of David Blackwell and Richard Tapia, two distinguished mathematical scientists who have been inspirations to more than a generation of African American, Latino/Latina, and Native American students and professionals in the mathematical sciences. It recognizes a mathematical scientist who has contributed and continues to contribute significantly to research in his or her field of expertise, and who has served as a role model for mathematical scientists and students from under-represented minority groups or contributed in other significant ways to addressing the problem of the under-representation of minorities in mathematics.

The prize will be awarded at the Fourth Blackwell-Tapia Conference, to be held at the IMA on November 3–4, 2006. The one and a half day meeting is designed to inform the next generation of mathematical scientists about career opportunities in mathematics and encourage them to network with other students and senior scientists. The conference program includes a mix of activities in which participants will share the excitement of mathematical research and its power to change our lives and the world around us.

IMA Events

IMA Annual Program Year Workshop

Visual Learning and Recognition

May 22-26, 2006

Organizers: Donald Geman (John Hopkins University), Jitendra Malik (University of California—Berkeley),
Shimon Ullman (The Weizmann Institute of Science)

Various mathematical frameworks have been explored for visual learning and visual recognition. Special cases of Bayesian modeling and inference, such as deformable templates and compositional vision, lead to the construction of probability measures on complex structures, such as grammars, graphs and spaces of transformations. Difficult mathematical questions arise in learning these and other representations from training data consisting of labeled examples. Recently, tools from statistical inference and information theory have led to new bounds on generalization error as well as new learning algorithms for classification. Most methods for interpreting complex scenes raise formidable computational challenges, inspiring new strategies for visual search. Despite stronger theoretical foundations, and despite progress in special cases of learning and recognition (e.g., in finding instances from one object class and in analyzing the limits of inductive learning), the full scene interpretation problem remains out of reach. The purpose of this workshop is to present and contrast differing proposals about central issues such as computation, tradeoffs in learning vs. modeling, connections with natural vision and the roles of classification, bottom-up processing (e.g., segmentation) and hierarchies of parts.

Workshop Strategy: The workshop will be somewhat unorthodox in the sense of departing from the usual n-talk format in favor of extensive discussion. Aside from one poster session and one session on "Neural Representation and Computation", which consists of talks from several people from the neuroscience community, the activities are either:
i) Strategy sessions, each about an approach or set of tools for visual recognition and involving two "advocates"and two "critics," and each of duration about two hours, or
ii) Discussion sessions about more general topics, each assigned several "panelists" and of duration one hour.
The advocates will describe the general strategy, or their variation on it, in the manner of a mini-tutorial, concentrating on mature work and the big picture. The critics will evaluate the approach, both the specific variations represented by the advocates as well as the general potential—strengths and weaknesses, inherent limitations, etc., everything that makes for constructive criticism; audience participation is encouraged.

Schedule

Monday, May 1

11:15a-12:15pSpecial Effects in Images and Video: Inpainting EverythingGuillermo R. Sapiro (University of Minnesota)EE/CS 3-125
2:30p-3:30pBiologically inspired algorithm development for computer-aided diagnosisBart M. ter Haar Romeny (Technical University of Eindhoven)Lind Hall 409

Tuesday, May 2

11:15a-12:15pProlate Spheroidal Sampling in Computerized TomographyTatiana Soleski (University of Minnesota)Lind Hall 409 PS

Friday, May 5

1:25p-2:25pShape and manifold modeling with nullspacesMatthew Brand (Mitsubishi Electric Research Labs)Room 20 Vincent Hall IPS

Tuesday, May 9

Monday, May 22

8:00a-8:45aRegistration and coffeeEE/CS 3-176 W5.22-26.06
8:45a-9:00aIntroductory remarksEE/CS 3-180 W5.22-26.06
9:00a-11:00aInvariant Local Descriptors
Advocate: Lazebnik
Critics: Huttenlocher, Malik
Dan Huttenlocher (Cornell University)
Svetlana Lazebnik (University of Illinois - Urbana-Champaign)
Jitendra Malik (University of California - Berkeley)
EE/CS 3-180 W5.22-26.06
11:00a-1:30pLunch W5.22-26.06
1:30p-2:30pRecognizing Actions and People
Panelists: Faugeras, Vidal, Soatto
Olivier Faugeras (INRIA - Sophia Antipolis Research Unit)
Stefano Soatto (University of California - Los Angeles)
Rene Vidal (Johns Hopkins University)
EE/CS 3-180 W5.22-26.06
2:30p-3:00pCoffeeEE/CS 3-176 W5.22-26.06
3:00p-5:00pLearning Shared Features
Advocates: Torralba, Ullman
Critics: Bienenstock, Riesenhuber
Elie Bienenstock (Brown University)
Max Riesenhuber (Georgetown University)
Antonio Torralba (Massachusetts Institute of Technology)
Shimon Ullman (The Weizmann Institute of Science)
EE/CS 3-180 W5.22-26.06
5:00p-6:00pReceptionLind Hall 400 W5.22-26.06

Tuesday, May 23

8:45a-9:00aCoffeeEE/CS 3-176 W5.22-26.06
9:00a-11:00aFlexible Templates
Advocates: Hinton, Felzenzwalb
Critics: Buhmann, LeCun
Joachim Buhmann (Swiss Federal Institute of Technology Zurich)
Pedro F. Felzenszwalb (University of Chicago)
Geoffrey E. Hinton (University of Toronto)
Yann LeCun (New York University)
EE/CS 3-180 W5.22-26.06
11:00a-1:30pLunch W5.22-26.06
1:30p-2:30pRecognizing Many Classes
Panelists: Perona, Ullman
Pietro Perona (California Institute of Technology)
Shimon Ullman (The Weizmann Institute of Science)
W5.22-26.06
2:30p-3:00pCoffeeEE/CS 3-176 W5.22-26.06
3:00p-5:00pHierarchical Testing
Advocates: Rehg, Geman
Critics: Hebert, Freeman
William T. Freeman (Massachusetts Institute of Technology)
Donald Geman (John Hopkins University)
Martial Hebert (Carnegie-Mellon University)
James Rehg (Georgia Institute of Technology)
EE/CS 3-180 W5.22-26.06

Wednesday, May 24

8:45a-9:00aCoffeeEE/CS 3-176 W5.22-26.06
9:00a-11:00aNeural Representation and ComputationKalanit Grill-Spector (Stanford University)
Nancy Kanwisher (Massachusetts Institute of Technology)
Manabu Tanifuji (Riken Brain Science Institute)
Simon Thorpe (CERCO)
EE/CS 3-180 W5.22-26.06
11:00a-1:30pLunch W5.22-26.06
1:30p-2:30pIt's a 3D World
Panelist: Jacobs
David Jacobs (University of Maryland)EE/CS 3-180 W5.22-26.06
2:30p-3:00pCoffeeEE/CS 3-176 W5.22-26.06
3:00p-5:00pPoster Session (Open)Lind Hall 400 W5.22-26.06
Hierarchical Statistical Learning of Generic Parts of Object StructureSanja Fidler (University of Ljubljana)

Thursday, May 25

8:45a-9:00aCoffeeEE/CS 3-176 W5.22-26.06
9:00a-11:00aGenerative Models
Advocates: Zhu, Amit
Critics: Malik, Weiss
Yali Amit (University of Chicago)
Jitendra Malik (University of California - Berkeley)
Yair Weiss (The Hebrew University of Jerusalem)
Song Chun Zhu ()
EE/CS 3-180 W5.22-26.06
11:00a-1:30pLunch W5.22-26.06
1:30p-2:30pThe Role of Information Theory
Panelists: O'Sullivan, Younes
Joseph A. O'Sullivan (Washington University - St. Louis)
Laurent Younes (Johns Hopkins University)
EE/CS 3-180 W5.22-26.06
2:30p-3:00pCoffeeEE/CS 3-176 W5.22-26.06
3:00p-5:00pHierarchies of Parts
Advocates: Poggio, Geman
Critics: Perona, Trouve
Stuart Geman (Brown University)
Pietro Perona (California Institute of Technology)
Tomaso Poggio (Massachusetts Institute of Technology)
Alain Trouve (Ecole Normale Superieure de Cachan)
EE/CS 3-180 W5.22-26.06

Friday, May 26

8:45a-9:00aCoffeeEE/CS 3-176 W5.22-26.06
9:00a-10:00aInsights from Neuroscience and Psychology
Panelists: Kersten, Valiant
Daniel Kersten (University of Minnesota)
Les Valiant (Harvard University)
EE/CS 3-180 W5.22-26.06
10:00a-11:00aIdentification vs. Categorization
Panelist: TBA
EE/CS 3-180 W5.22-26.06
11:00a-11:15aCoffeeEE/CS 3-176 W5.22-26.06
12:00p-1:00pTools or Theory?
Panelists: Azencott, Geman
Robert Azencott (Ecole Normale Superieure de Cachan)
Donald Geman (John Hopkins University)
EE/CS 3-180 W5.22-26.06
Abstracts
Matthew Brand (Mitsubishi Electric Research Labs) Shape and manifold modeling with nullspaces
Abstract: The surface of one's face is a 2d manifold embedded in 3d space; the space of all faces and facial expressions is a manifold with perhaps a few hundred statistically significant dimensions. These are very useful manifolds. Inconveniently, we have access to these manifolds only through their unknown immersions in the much higher-dimensional space of all possible (retinal) images. This motivates the problem of characterizing a manifold from data — usually a sparse sample of discrete points, tangents, or local geodesic distances. I'll outline a remarkably straightforward method that uses nullspace computations to separate variation on the manifold from variation due to the immersion, and connect this solution to practical problems in data analysis, projective geometry, and graph embeddings. The talk will be peppered with examples from facial coding and synthesis, shape-from-silhouettes problems, acoustic modeling of vowels, and computer graphics.
Sanja Fidler (University of Ljubljana) Hierarchical Statistical Learning of Generic Parts of Object Structure
Abstract: In collaboration with Leonardis, Ales, and Berginc, Gregor.

With the growing interest in object categorization various methods have emerged that perform well in this challenging task, yet are inherently limited to only a moderate number of object classes. In pursuit of a more general categorization system our framework proposes a way to overcome the computational complexity encompassing the enormous number of different object categories by exploiting the statistical properties of the highly structured visual world. Our approach proposes a hierarchical acquisition of generic parts of object structure, varying from simple to more complex ones, which stem from the favorable statistics of natural images. The parts recovered in the individual layers of the hierarchy can be used in a top-down manner resulting in a robust statistical engine that could be efficiently used within many of the current categorization systems. The proposed approach has been applied to large image datasets yielding important statistical insights into the generic parts of object structure.

Peter Philip (University of Minnesota) A Quasistatic Crack Propagation Model Allowing for Cohesive Forces and Crack Reversibility Using Local Energy Minimization
Abstract: While the classical theory of Griffith is the foundation of modern understanding of brittle fracture, it has a number of significant shortcomings: Griffith theory does not predict crack initiation and path and it suffers from the presence of unphysical stress singularities. In 1998, Francfort and Marigo presented an energy funtional minimization method, where the crack (or its absence) as well as its path are part of the problem's solution. The energy functionals act on spaces of functions of bounded variations, where the cracks are related to the discontinuity sets of such functions. The new model presented here uses modified energy functionals to account for Barenblatt cohesive forces such that the model becomes free of stress singularities. This is done in a physically consistent way using recently published concepts of Sinclair. Here, for the consistency of the model, it becomes necessary to allow for crack reversibility and to consider local minimizers of the energy functionals. The latter is achieved by introducing different time scales. Finally, for some simple examples, the new model is solved and the results are compared to corresponding results using previously existing models.
Guillermo R. Sapiro (University of Minnesota) Special Effects in Images and Video: Inpainting Everything
Abstract: In this talk I will describe results on image and video manipulation, including image and video inpainting and colorization. I will show how fundamental mathematics lead to state-of-the-art and fast algorithms for image and video processing.
Tatiana Soleski (University of Minnesota) Prolate Spheroidal Sampling in Computerized Tomography
Abstract: In Computerized Tomography (CT), an image must be reconstructed from data given by the Radon transform of the image. In this talk we introduce a method of recovering the image based on the sampling properties of the Prolate Spheroidal wavelets (PS-wavelets) which are superior to other wavelet systems. It avoids integration and allows the precomputation of certain coefficients. The approximation based on this method is shown to converge to the true image under mild hypotheses. The algorithm is then tested on the standard Shepp-Logan image and is shown to be surprisingly good.

Another interesting issue is related to the construction of the above mentioned wavelets. The standard way of calculating their values uses an approximation based on Legendre polynomials and Bessel functions. We present a new method based on an eigenvalue problem for a matrix operator equivalent to that of the integral operator associated with the PS-wavelets. Its solution gives the values of these functions on the entire real line and is computationally more efficient.

Bart M. ter Haar Romeny (Technical University of Eindhoven) Biologically inspired algorithm development for computer-aided diagnosis
Abstract: Due to the overwhelming production of medical images there is an increasing demand.to the design of effective methods for computer-aided diagnosis and quantitative analysis. In the lecture we discuss how bio-mimicking the early stages of vision can give new inspiration for the design of image analysis algorithms.

The multi-scale and multi-orientation approach of the front-end visual system has become clear from psychophysical, neurophysiological and voltage-sensitive dye measurements. We will discuss the early visual stages as a mechanism / model, to do robust high order differential geometry on images, to perform perceptual grouping with oriented wavelets, and to extract subscenes from a scene with multi-scale singularity points.

The design of these algorithms is facilitated by the use of Mathematica as a high level analysis and visualization software.

Visitors in Residence
In Soo Ahn Bradley University 5/21/2006 - 5/25/2006
Yali Amit University of Chicago 5/21/2006 - 5/26/2006
Jung-Ha An University of Minnesota 9/1/2005 - 8/31/2007
Pablo Arias Universidad de la Republica 5/21/2006 - 5/27/2006
Douglas N. Arnold University of Minnesota 7/15/2001 - 8/31/2010
Donald G. Aronson University of Minnesota 9/1/2002 - 8/31/2006
Robert Azencott Ecole Normale Superieure de Cachan 5/21/2006 - 5/26/2006
Evgeniy Bart University of Minnesota 9/1/2005 - 8/31/2007
Elie Bienenstock Brown University 5/21/2006 - 5/26/2006
Michael Bieterman Boeing Company 5/21/2006 - 5/26/2006
Francisco Blanco-Silva Purdue University 9/1/2005 - 6/30/2006
Daniel Boley University of Minnesota 5/22/2006 - 5/26/2006
Matthew Brand Mitsubishi Electric Research Labs 5/4/2006 - 5/5/2006
Joachim Buhmann Swiss Federal Institute of Technology Zurich 5/20/2006 - 5/27/2006
Stefan Carlsson KTH 5/21/2006 - 5/26/2006
Albert Chan Fayetteville State University 5/21/2006 - 5/27/2006
Igor Chechelnitsky University of Minnesota 5/22/2006 - 5/26/2006
Qianyong Chen University of Minnesota 9/1/2004 - 8/31/2006
Li Cheng National ICT Australia 5/21/2006 - 5/26/2006
Jose Antonio Costa California Institute of Technology 5/21/2006 - 5/26/2006
Steven Benjamin Damelin Georgia Southern University 8/9/2005 - 6/30/2006
James Damon University of North Carolina 3/3/2006 - 6/30/2006
Declan Davis University of Liverpool 4/9/2006 - 5/9/2006
Brian DiDonna University of Minnesota 9/1/2004 - 8/31/2006
Oliver Dorn Universidad Carlos III de Madrid 4/4/2006 - 6/2/2006
Julio Duarte University of Puerto Rico at Mayaguez 5/21/2006 - 5/27/2006
Jinwoo Eo University of Minnesota 5/21/2006 - 5/26/2006
Olivier Faugeras INRIA - Sophia Antipolis Research Unit 5/21/2006 - 5/26/2006
Li Fei-Fei University of Illinois - Urbana-Champaign 5/21/2006 - 5/27/2006
Pedro F. Felzenszwalb University of Chicago 5/1/2006 - 5/30/2006
Sanja Fidler University of Ljubljana 5/20/2006 - 5/27/2006
Francois Fleuret Ecole Polytechnique Federale de Lausanne 5/21/2006 - 5/26/2006
William T. Freeman Massachusetts Institute of Technology 5/21/2006 - 5/26/2006
Bastian Gebauer Johannes Gutenberg University of Mainz 5/11/2006 - 6/11/2006
Donald Geman John Hopkins University 5/17/2006 - 5/26/2006
Stuart Geman Brown University 5/21/2006 - 5/26/2006
Peter Giblin University of Liverpool 4/9/2006 - 5/9/2006
Maria Gini University of Minnesota 5/22/2006 - 5/26/2006
Alvina Goh John Hopkins University 5/21/2006 - 5/26/2006
David Gray Air Force Research Laboratory 5/21/2006 - 5/26/2006
Kalanit Grill-Spector Stanford University 5/21/2006 - 5/26/2006
Raffaele Grompone CMLA, ENS of Cachan 5/21/2006 - 5/27/2006
Changfeng Gui University of Connecticut 9/12/2005 - 6/30/2006
Jooyoung Hahn KAIST 8/26/2005 - 7/31/2006
Hazem Hamdan University of Minnesota 5/22/2006 - 5/26/2006
Gloria Haro Ortega University of Minnesota 9/1/2005 - 8/31/2007
Martial Hebert Carnegie-Mellon University 5/21/2006 - 5/26/2006
Geoffrey E. Hinton University of Toronto 5/21/2006 - 5/26/2006
Byung-Woo Hong University of California - Los Angeles 5/22/2006 - 5/26/2006
Xiang Huang University of Connecticut 9/1/2005 - 6/30/2006
Dan Huttenlocher Cornell University 5/21/2006 - 5/26/2006
Camille Izard John Hopkins University 5/21/2006 - 5/27/2006
Paul Jackway CSIRO 5/22/2006 - 5/26/2006
David Jacobs University of Maryland 5/21/2006 - 5/26/2006
Bruno Jedynak Johns Hopkins University 5/21/2006 - 5/26/2006
Sookyung Joo University of Minnesota 9/1/2004 - 8/31/2006
Fredrik Kahl Lund University 5/21/2006 - 5/27/2006
Sung Ha Kang University of Kentucky 1/1/2006 - 5/31/2006
Nancy Kanwisher Massachusetts Institute of Technology 5/21/2006 - 5/26/2006
Chiu Yen Kao University of Minnesota 9/1/2004 - 8/31/2006
Daniel Kersten University of Minnesota 5/21/2006 - 5/26/2006
Matthias Kurzke University of Minnesota 9/1/2004 - 7/1/2006
Song-Hwa Kwon University of Minnesota 8/30/2005 - 8/31/2007
Svetlana Lazebnik University of Illinois - Urbana-Champaign 5/21/2006 - 5/26/2006
Yann LeCun New York University 5/21/2006 - 5/26/2006
Chang-Ock Lee KAIST 8/1/2005 - 7/31/2006
Stacey E. Levine Duquesne University 12/30/2005 - 6/30/2006
Debra Lewis University of Minnesota 7/15/2004 - 8/31/2006
Hstau Liao University of Minnesota 9/2/2005 - 8/31/2007
Bradley J. Lucier Purdue University 8/15/2005 - 6/15/2006
Kirsi Majava University of Jyväskylä 5/18/2006 - 5/27/2006
Alison Malcolm University of Minnesota 9/1/2005 - 8/31/2006
Jitendra Malik University of California - Berkeley 5/21/2006 - 5/26/2006
Riccardo March Consiglio Nazionale delle Ricerche 4/1/2006 - 5/1/2006
Md. Maruf Monwar University of Northern British Columbia 5/20/2006 - 5/28/2006
Jeremy Neal Kent State University 8/8/2004 - 8/19/2009
Juan Carlos Niebles University of Illinois - Urbana-Champaign 5/20/2006 - 5/28/2006
Partha Niyogi University of Chicago 5/21/2006 - 5/26/2006
Peter J. Olver University of Minnesota 9/1/2005 - 6/30/2006
Katerina Papoulia Cornell University 5/3/2006 - 5/7/2006
Pietro Perona California Institute of Technology 5/21/2006 - 5/26/2006
Peter Philip University of Minnesota 8/22/2004 - 8/31/2006
Peter Philip University of Minnesota 5/6/2006 - 5/14/2006
Tomaso Poggio Massachusetts Institute of Technology 5/21/2006 - 5/26/2006
Gregory J. Randall Universidad de la Republica 8/18/2005 - 7/31/2006
James Rehg Georgia Institute of Technology 5/21/2006 - 5/26/2006
Walter Richardson Jr. University of Texas - San Antonio 9/1/2005 - 6/30/2006
Max Riesenhuber Georgetown University 5/21/2006 - 5/26/2006
Stergios I. Roumeliotis University of Minnesota 5/22/2006 - 5/26/2006
Fadil Santosa University of Minnesota 9/1/2005 - 6/30/2006
Guillermo R. Sapiro University of Minnesota 9/1/2005 - 6/30/2006
Arnd Scheel University of Minnesota 7/15/2004 - 8/31/2006
Jin Keun Seo Yonsei University 1/5/2006 - 6/5/2006
Dheeraj Prasad Singaraju John Hopkins University 5/21/2006 - 5/26/2006
Stefano Soatto University of California - Los Angeles 5/21/2006 - 5/26/2006
Tatiana Soleski University of Minnesota 9/1/2005 - 8/31/2007
Vladimir Sverak University of Minnesota 9/1/2005 - 6/30/2006
Manabu Tanifuji Riken Brain Science Institute 5/21/2006 - 5/26/2006
Roberto Facundo Memoli Techera Stanford University 5/21/2006 - 5/27/2006
Bart M. ter Haar Romeny Technical University of Eindhoven 4/23/2006 - 5/21/2006
Simon Thorpe CERCO 5/20/2006 - 5/26/2006
Carl Toews University of Minnesota 9/1/2005 - 8/31/2007
Antonio Torralba Massachusetts Institute of Technology 5/21/2006 - 5/26/2006
Alain Trouve Ecole Normale Superieure de Cachan 5/21/2006 - 5/26/2006
Shimon Ullman The Weizmann Institute of Science 5/21/2006 - 5/26/2006
Les Valiant Harvard University 5/21/2006 - 5/26/2006
Miguel Velez-Reyes University of Puerto Rico at Mayaguez 5/21/2006 - 5/26/2006
Rene Vidal Johns Hopkins University 5/14/2006 - 5/28/2006
Michel Vidal-Naquet Riken Brain Science Institute 5/21/2006 - 5/26/2006
Rossmary Villegas Universidad Carlos III de Madrid 5/1/2006 - 5/31/2006
Jingyue Wang Purdue University 9/1/2005 - 6/30/2006
Xiaoqiang Wang University of Minnesota 9/1/2005 - 8/8/2006
Yair Weiss The Hebrew University of Jerusalem 5/21/2006 - 5/26/2006
Laurent Younes Johns Hopkins University 5/21/2006 - 5/26/2006
William Yurcik University of Illinois - Urbana-Champaign 5/21/2006 - 5/26/2006
Ofer Zeitouni University of Minnesota 9/1/2005 - 6/30/2006
Song Chun Zhu University of California - Los Angeles 5/21/2006 - 5/23/2006
Legend: Postdoc or Industrial Postdoc Long-term Visitor

Participating Institutions: Air Force Research Laboratory, Carnegie-Mellon University, Consiglio Nazionale delle Ricerche, Georgia Institute of Technology, Indiana University, Iowa State University, Kent State University, Lawrence Livermore National Laboratories, Los Alamos National Laboratory, Michigan State University, Mississippi State University, Northern Illinois University, Ohio State University, Pennsylvania State University, Purdue University, Rice University, Rutgers University, Sandia National Laboratories, Seoul National University, Texas A & M University, University of Chicago, University of Cincinnati, University of Delaware, University of Houston, University of Illinois - Urbana-Champaign, University of Iowa, University of Kentucky, University of Maryland, University of Michigan, University of Minnesota, University of Notre Dame, University of Pittsburgh, University of Texas - Austin, University of Wisconsin - Madison, University of Wyoming, Wayne State University
Participating Corporations: 3M, Boeing, Corning, ExxonMobil, Ford, General Electric, General Motors, Honeywell, IBM, Johnson & Johnson, Lockheed Martin, Medtronic, Motorola, Schlumberger, Siemens, Telcordia